To make an automated or partially automated control of a motor vehicle possible, sensors are customarily used to scan an area surrounding the motor vehicle to determine the location of obstacles with which the motor vehicle should not collide. For that purpose, the surrounding area is usually theoretically subdivided into a regular grid, and, for each cell of the grid, whether an obstacle is located therein is determined The thus acquired information is transferred to an obstacle map that includes a number of grid points whose placement corresponds to that of the cells of the area surrounding the motor vehicle. A grid point is identified that corresponds to a cell that is occupied to more than a predefined degree.
On the basis of the obstacle map, how the motor vehicle is to be controlled to avoid a collision with one of the obstacles can subsequently be determined To that end, in particular, which cells will be occupied at a future point in time can be determined This also makes it possible to avoid a collision with any arbitrary object.
A technology of this kind is described, for example, in T. Gindele et al., “Bayesian Occupancy Grid Filter for Dynamic Environments Using Prior Map Knowledge,” IEEE Intelligent Vehicles Symposium, pp. 669-676, China (2009).